Modern technology offers data storage systems that store massive amounts of data in many different formats. Databases, data servers, and other devices store data that represents nearly every facet of digital society. One prevalent format includes character delimited values files. For example, a text file may include many rows of data where each row includes a set of values delimited or separated by commas, or another character. Such a file format may be easier for a human to read and may provide a standard data format, making migration from one data storage system to another less complex.
However, a character delimited data file suffers from several drawbacks. First, such a file is not well compressed causing the data to occupy more storage space than necessary. Of course, such a file may be compressed to reduce storage space; however, the file generally would need to be uncompressed in order to access values stored in the file.
Second, because varying values occupy different lengths in the data file, data values would generally need to be read in order to access certain values. For example, in order to determine the 10th value, the previous nine values would generally need to be read. Furthermore, in order to read a value in the 100th row, the previous 99 rows would generally need to be read by a data processing system. Therefore, accessing data in a character delimited value file is much slower than other, more native formats.